Study On Screen Classification Characteristics Of Three-product Cyclone Classification Screen

Nowadays, the technology of fine coal classification is a hot issue in the study of mineral processing field. As a new-type and high-efficiency device for fine coal classification, the three-product cyclone classification screen has an important research value and application prospect. The core content of the study is screen sizing characteristic, the conclusion which guide the industrial production can be achieved by theoretical analysis and experimental research.The theoretical analysis aims to describe the motion of two phase flow in the three-product cyclone classification screen, guide the experimental research and industrial application.One side, based on the achievement and hydromechamics knowledge, the paper ayalysises the kinetic characteristic of the interal liquid fulid and solid particle to find the rule of velocity, pressure and solid particle. On the other side, using structural features,the paper divides the whole classification process into swirling flow classification and screen classification,and the key point is screen classification. With the help of the sieve bend theory, the working principle and classification theory can be expounded, the theory through size formula and screen classification size formula can be deduced.The experimental research intends to sum up the experimental conclusion of three-product cyclone classification screen, prove the theoretical analysis, use in the industrial production as a production rule. First, the paper chooses the feed concentration, the feed pressure, the underflow opening diameter and the interaction effect to carry out orthogonal experiment, to gain the rule of their remarkable influence to the whole and screen classification evaluation index. The result indicates the interaction of the feed concentration and underflow opening diameter is the most remarkable factor. Then, the experimental study on the interaction of the feed concentration and underflow opening diameter can get the rule of the factor’s influence to the classification evaluation index. According to the data analysis, the optimum matching relation of the feed concentration and underflow opening diameter can be find, whose unary linear regression equation is ? 6 6, and the relation shows the ideal classification effect will appear when the screen flow division ratio in 68~70%. Finally, applying the arranged experimental data, the paper builds mathematical model by the BP neural networks, which uses the working condition as input parameters and the classification evaluation index as output parameters. The verification and analysis show the global error is 8.49%. It can achieve the accuracy requirement in industrial production.In this paper four hypothesis are raised to explain this phenomenon and provides clue for later study. Research findings in this paper provides a basis for three-product swirl classification screen for further study, and is a impetus for the device to utilize in the industry.